Numerical Algorithms for Modern Parallel Computer Architectures

1. Front Matter

   Pages i-xi

   PDF

2. Parallelization of Physical Systems on the BBN Butterfly: Some Examples

   • William Celmaster

   Pages 1-9

3. Solution of Large Scale Engineering Problems Using a Loosely Coupled Array of Processors

   • E. Clementi, D. Logan, V. Sonnad

   Pages 11-27

4. A Look at the Evolution of Mathematical Software for Dense Matrix Problems over the Past Fifteen Years

   • J. J. Dongarra, D. C. Sorensen

   Pages 29-36

5. A Graphical Approach to Load Balancing and Sparse Matrix Vector Multiplication on the Hypercube

   • Geoffrey C. Fox

   Pages 37-61

6. A Review of Automatic Load Balancing and Decomposition Methods for the Hypercube

   • Geoffrey C. Fox

   Pages 63-76

7. Adaptive Methods for Hyperbolic Problems on Local Memory Parallel Processors

   • William Gropp

   Pages 77-84

8. Systolic Algorithms for the Parallel Solution of Dense Symmetric Positive-Definite Toeplitz Systems

   • Ilse C. F. Ipsen

   Pages 85-108

9. Ensemble Architectures and their Algorithms: An Overview

   • S. Lennart Johnsson

   Pages 109-144

10. Problem Decomposition and Communication Tradeoffs in a Shared-Memory Multiprocessor

    • Thomas J. LeBlanc

    Pages 145-162

11. Domain Decomposition Preconditioners for Elliptic Problems in Two and Three Dimensions

    • Joseph E. Pasciak

    Pages 163-171

12. Methods for Automated Problem Mapping

    • Joel Saltz

    Pages 173-195

13. Block Algorithms for Parallel Machines

    • Robert Schreiber

    Pages 197-207

14. The LCAP System: An Example of a Multicomputer

    • Martin H. Schultz

    Pages 209-216

15. A Block QR Factorization Scheme for Loosely Coupled Systems of Array Processors

    • Charles van Loan

    Pages 217-232

Parallel computers have started to completely revolutionize scientific computation. Articles in this volume represent applied mathematics, computer science, and application aspects of parallel scientific computing. Major advances are discussed dealing with multiprocessor architectures, parallel algorithm development and analysis, parallel systems and programming languages. The optimization of the application of massively parallel architectures to real world problems will provide the impetus for the development of entirely new approaches to these technical situations.

• Evolution
• Scheme
• Sparse matrix
• computer
• computer architecture
• optimization
• programming
• science
• scientific computing

• Research Center for Scientific Computation, Yale University, New Haven, USA

  Martin Schultz

Policies and ethics